Stock Market News

US FTC looking into targeted pricing based on personal data

2024.07.23 12:31

By Jody Godoy

(Reuters) – The U.S. Federal Trade Commission has launched a study of products that could allow companies to set different prices for consumers based on their locations, past purchases, and other personal data.

The agency said on Tuesday it had ordered Mastercard (NYSE:), JPMorgan Chase (NYSE:), and six other companies to provide information about targeted pricing products, the data they use, who uses them and the effect on prices.

The FTC is seeking the same information from IT services provider Accenture (NYSE:), consulting firm McKinsey & Co., and software providers Pros Holdings Inc, Revionics, Bloomreach, and Task Software.

All of the companies offer products that use consumer data and artificial intelligence or other technology to target prices for individual consumers, the agency said. None of the companies are accused of wrongdoing.

FTC Chair Lina Khan said the study will illuminate a “shadowy ecosystem of pricing middlemen.”

“Firms that harvest Americans’ personal data can put people’s privacy at risk. Now firms could be exploiting this vast trove of personal information to charge people higher prices,” Khan said in a statement.

Online advertising has long used data such as browsing history and device location to determine what ads consumers see.

© Reuters. FILE PHOTO: A hand is seen on a laptop with binary codes displayed in front of the USA flag in this illustration taken, August 19, 2022. REUTERS/Dado Ruvic/Illustration/File Photo

The agency is concerned similar technology can now be used to set disparate prices, which it calls “surveillance pricing,” or potentially collude with competitors, FTC officials said.

The FTC is already considering rules aimed at protecting consumer privacy and limit what data businesses can collect without consent.



Source link

Related Articles

Back to top button
bitcoin
Bitcoin (BTC) $ 94,245.25 1.56%
ethereum
Ethereum (ETH) $ 3,338.87 0.22%
tether
Tether (USDT) $ 0.998633 0.03%
xrp
XRP (XRP) $ 2.15 0.57%
bnb
BNB (BNB) $ 694.37 0.94%
solana
Solana (SOL) $ 184.91 2.09%
dogecoin
Dogecoin (DOGE) $ 0.313395 0.16%
usd-coin
USDC (USDC) $ 1.00 0.02%
staked-ether
Lido Staked Ether (STETH) $ 3,335.59 0.18%
cardano
Cardano (ADA) $ 0.872886 1.09%
tron
TRON (TRX) $ 0.262309 3.31%
avalanche-2
Avalanche (AVAX) $ 36.61 1.99%
the-open-network
Toncoin (TON) $ 5.75 0.22%
wrapped-steth
Wrapped stETH (WSTETH) $ 3,963.81 0.22%
chainlink
Chainlink (LINK) $ 21.41 5.91%
shiba-inu
Shiba Inu (SHIB) $ 0.000022 0.62%
wrapped-bitcoin
Wrapped Bitcoin (WBTC) $ 94,131.22 1.37%
sui
Sui (SUI) $ 4.06 3.61%
bitget-token
Bitget Token (BGB) $ 8.28 9.42%
stellar
Stellar (XLM) $ 0.349468 1.95%
hedera-hashgraph
Hedera (HBAR) $ 0.27541 3.34%
polkadot
Polkadot (DOT) $ 6.90 1.00%
weth
WETH (WETH) $ 3,338.03 0.30%
hyperliquid
Hyperliquid (HYPE) $ 26.41 4.58%
bitcoin-cash
Bitcoin Cash (BCH) $ 441.29 0.77%
leo-token
LEO Token (LEO) $ 9.20 0.33%
uniswap
Uniswap (UNI) $ 13.27 1.11%
litecoin
Litecoin (LTC) $ 100.22 2.36%
pepe
Pepe (PEPE) $ 0.000018 2.61%
wrapped-eeth
Wrapped eETH (WEETH) $ 3,522.58 0.22%
near
NEAR Protocol (NEAR) $ 5.12 0.17%
ethena-usde
Ethena USDe (USDE) $ 0.997417 0.02%
usds
USDS (USDS) $ 1.00 0.13%
internet-computer
Internet Computer (ICP) $ 10.22 1.10%
aave
Aave (AAVE) $ 324.08 4.23%
aptos
Aptos (APT) $ 8.71 1.82%
polygon-ecosystem-token
POL (ex-MATIC) (POL) $ 0.479327 0.43%
crypto-com-chain
Cronos (CRO) $ 0.148061 1.88%
mantle
Mantle (MNT) $ 1.19 0.85%
ethereum-classic
Ethereum Classic (ETC) $ 25.94 0.34%
vechain
VeChain (VET) $ 0.045937 1.93%
render-token
Render (RENDER) $ 7.00 1.83%
monero
Monero (XMR) $ 194.90 3.28%
mantra-dao
MANTRA (OM) $ 3.72 1.55%
whitebit
WhiteBIT Coin (WBT) $ 24.60 0.28%
virtual-protocol
Virtuals Protocol (VIRTUAL) $ 3.45 15.26%
bittensor
Bittensor (TAO) $ 468.98 0.54%
dai
Dai (DAI) $ 0.999693 0.02%
fetch-ai
Artificial Superintelligence Alliance (FET) $ 1.30 2.03%
arbitrum
Arbitrum (ARB) $ 0.759321 0.38%